Do we attribute intentional agency to humanoid robots?
Agnieszka Wykowska Istituto Italiano Di Tecnologia Genoa, Italy
UQÀM ISC DIC CRIA Cognitive Informatics Seminar Séminaire en informatique cognitive
Thursday, 10:30 am ET (Montreal time) October 6, 2022 Zoom: https://uqam.zoom.us/j/88481835073
Abstract: When predicting and explaining the behavior of other humans, we adopt the intentional stance, and refer to mental states in order to understand others’ actions. It is not clear, however, whether and when we adopt the intentional stance also towards artificial agents, such as humanoid robots. This talk will provide an overview of research conducted in my lab which addresses this question. I will present a tool for measuring the adoption of the intentional stance. The likelihood of adopting the intentional stance is coded in specific patterns of neural activity at rest. Interactive scenarios influence adoption of the intentional stance more than mere observation of subtle human-like characteristics of a robot’s behavior. Experiments using interactive joint action protocols with a humanoid robot to study the vicarious and joint sense of agency show that the robots’ motor repertoire and our ability to represent its actions with our own sensorimotor repertoire influence the vicarious sense of agency. Embedding a non-verbal adaptation of a “Turing test” In a human-robot joint action task showed that human-like variability in the robot’s simple button presses makes the robot pass the test. The talk will conclude with a discussion of the role of the intentional stance and sense of agency in other mechanisms of social cognition, and their implications in applied domains of social robotics in healthcare.
References:
Bossi, F., Willemse, C., Cavazza, J., Marchesi, S., Murino, V., Wykowska, A. (2020). The human brain reveals resting state activity patterns that are predictive of biases in attitudes towards robots. Science Robotics, 5:46, eabb6652: https://www.science.org/doi/10.1126/scirobotics.abb6652 Marchesi, S., De Tommaso, D., Perez-Osorio, J., Wykowska A. (2022). Belief in sharing the same phenomenological experience increases the likelihood of adopting the intentional stance towards a humanoid robot. Technology, Mind and Behavior, 3(3): https://www.apa.org/pubs/journals/releases/tmb-tmb0000072.pdf Ciardo, F., De Tommaso, D., Wykowska, A. (2022). Human-like behavioural variability blues the distinction between a human and a machine in a nonverbal Turing test. Science Robotics, 7, eabo 1241: https://www.science.org/doi/10.1126/scirobotics.abo1241 Roselli, C., Ciardo, F., De Tommaso, D., Wykowska, A. (2022). Human‐likeness and attribution of intentionality predict vicarious sense of agency over humanoid robot actions. Nature: Scientific Reports, 12:13845: https://www.nature.com/articles/s41598-022-18151-6.pdf Note: for the papers behind paywall, please visit our website, where you can find access links to all papers: https://instanceproject.eu/publications/list-of-publications
Professor Agnieszka Wykowska leads the unit “Social Cognition in Human-Robot Interaction” at the Italian Institute of Technology (Genoa, Italy). The research foci of Prof. Wykowska are interdisciplinary, bridging psychology, cognitive neuroscience, robotics and healthcare. She combines cognitive neuroscience methods with human-robot interaction to understand the human brain mechanisms in interaction with other humans and with robots. Her research is also dedicated to applications of social robotics to healthcare: her team develops robot-assisted training protocols to help children diagnosed with autism-spectrum disorder in improving social skills.
08-Sep Bernard Baars Conscious computing is only a metaphor 15-Sep Jean-Pierre Briot Music creation with deep learning technique 22-Sep Mehdi Khamassi Active exploration in reinforcement learning 29-Sep Murray Shanahan Animal cognition and AI 06-Oct Agnieszka Wykowska Do we attribute intentional agency to humanoid robots? 20-Oct Christian Lebière Cognitive architectures and their applications 03-Nov Baptiste Caramiaux Interactive Machine Learning: Principles and Applications 10-Nov Lorenzo Natale AI/robotics and active visual and tactile perception 17-Nov Ziemke, Tom The observer’s grounding problem in human-robot interaction 24-Nov Christian Keysers Neural Basis of Empathy and Prosociality Across Species 01-Dec Katy Börner Atlas of Forecasts: Modeling and Mapping Desirable Futures 08-Dec Karl Friston Active inference and artificial curiosity 15-Dec Todd Gureckis Intuitive Physical Reasoning and Mental Simulation
Cognitive architectures and their applications Christian Lebière Psychology, Carnegie-Mellon University
UQÀM ISC DIC CRIA Cognitive Informatics Seminar / Cognitive Informatics Seminar
Thursday, 10:30 am ET October 20, 2022 Zoom: https://uqam.zoom.us/j/88481835073 Abstract: Cognitive architectures are computational implementations of unified theories of cognition. Being able to represent human cognition in computational form enables a wide range of applications when humans and machines interact. Using cognitive models to represent common ground between deep learners and human users enables adaptive explanations. Cognitive models representing the behavior of cyber attackers can be used to optimize cyber defenses including techniques such as deceptive signaling. Cognitive models of human-automation interaction can improve robustness of human-machine teams by predicting disruptions to measures of trust under various adversarial situations. Finally, the consensus of 50 years of research in cognitive architectures can be captured in the form of a Common Model of Cognition that can provide a guide for neuroscience, artificial intelligence and robotics. [A person wearing glasses Description automatically generated with medium confidence] Christian Lebiere, Research Faculty, CMU, works on cognitive architectures and their applications to psychology, artificial intelligence, human-computer interaction, decision-making, intelligent agents, network science, cognitive robotics and neuromorphic engineering.
Cranford, E. A., Gonzalez, C., Aggarwal, P., Tambe, M., Cooney, S., & Lebiere, C. (2021). Towards a cognitive theory of cyber deceptionhttps://www.cmu.edu/dietrich/sds/ddmlab/papers/CranfordGonzalezAggarwalTambeCooneyLebiere2021.pdf. Cognitive Science, 45(7), e13013.
Cranford, E., Gonzalez, C., Aggarwal, P., Cooney, S., Tambe, M., & Lebiere, C. (2020). Adaptive cyber deception: Cognitively informed signaling for cyber defensehttps://www.cmu.edu/dietrich/sds/ddmlab/papers/CranfordAggarwalGonzalezCooneyTambeLebiere2020.pdf.
Lebiere, C., Blaha, L. M., Fallon, C. K., & Jefferson, B. (2021). Adaptive cognitive mechanisms to maintain calibrated trust and reliance in automationhttps://www.frontiersin.org/articles/10.3389/frobt.2021.652776/full. Frontiers in Robotics and AI, 8, 652776.
Laird, J. E., Lebiere, C., & Rosenbloom, P. S. (2017). A standard model of the mind: Toward a common computational framework across artificial intelligence, cognitive science, neuroscience, and roboticshttps://www.proquest.com/docview/1987347010?pq-origsite=gscholar&fromopenview=true. AI Magazine, 38(4), 13-26.
Lebiere, C., Pirolli, P., Thomson, R., Paik, J., Rutledge-Taylor, M., Staszewski, J., & Anderson, J. R. (2013). A functional model of sensemaking in a neurocognitive architecturehttp://act-r.psy.cmu.edu/wordpress/wp-content/uploads/2015/09/ICArUS-Model-Details-Computational-Intelligence-and-Neuroscience-Special-Issue.pdf. Computational Intelligence and Neuroscience, 2013.
Interactive Machine Learning: Principles and Applications
Baptiste Caramiaux https://hci.isir.upmc.fr/https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhci.isir.upmc.fr%2F&data=05%7C01%7Charnad%40ecs.soton.ac.uk%7C4a09625327b041dde3de08da9be3928d%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637993700149326634%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000%7C%7C%7C&sdata=gD55fCohLWRD78la7qpYDpLKTWAAB2nCmwgMpP8OxgU%3D&reserved=0 CNRS researcher. Institute of Intelligent Systems and Robotics, Sorbonne
UQÀM ISC DIC CRIA Séminaire en informatique cognitive/Cognitive Informatics Seminar Thursday, 10:30 am (Paris 16h30) November 3, 2022 Zoom: https://uqam.zoom.us/j/88481835073
Abstract: Machine learning algorithms are present in many of the applications and services we use every day. These technologies are often designed in isolation from their users, leading to a standardisation of their uses and a centralised control of their capabilities. Creating learning technologies that are closer to people and their context of use opens up the possibility of more responsive, appropriable and inclusive interactions. In this talk, I will present the context and the research community working on these themes at the intersection between HCI and AI. Then I will focus on my work in this field. I will show examples of research where the artistic approach is sometimes seen as a tool to reflect on technologies as cultural actors, and sometimes seen as a tool to inspire the design of rich and expressive interactions. Finally, I will present concrete ways to design interactions with machine learning algorithms through the concept of Machine Teaching.
Bio: Baptiste Caramiaux is a CNRS researcher at ISIR, Sorbonne Université in Paris, in the HCI Sorbonne group. He conducts research in human-computer interaction (HCI), studying and designing interactions with machine learning algorithms in the context of performing arts, health and pedagogy.
References:
Caramiaux, B., Altavilla, A., Françoise, J., & Bevilacqua, F. (2022, June). Gestural Sound Toolkit: Reflections on an Interactive Design Projecthttps://nime.pubpub.org/pub/vpgn52hr/release/1?readingCollection=8d5ef7ab. In International Conference on New Interfaces for Musical Expression. PubPub.
Caramiaux, B., Alaoui, S. F., & Hsueh, S. (2022, April). What Becomes of" Work" in AI" Artwork"https://scholar.google.com/scholar?as_ylo=2022&q=author:%22caramiaux+baptiste%22&hl=en&as_sdt=0,5?. In CHI'22 Conference-Workshop on Outsourcing Artificial Intelligence: Responding to the Reassertion of the Human Element into Automation.
Interactive Machine Learning: Principles and Applications
Baptiste Caramiaux https://hci.isir.upmc.fr/https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhci.isir.upmc.fr%2F&data=05%7C01%7Charnad%40ecs.soton.ac.uk%7C4a09625327b041dde3de08da9be3928d%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637993700149326634%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C2000%7C%7C%7C&sdata=gD55fCohLWRD78la7qpYDpLKTWAAB2nCmwgMpP8OxgU%3D&reserved=0 CNRS researcher. Institute of Intelligent Systems and Robotics, Sorbonne
UQÀM ISC DIC CRIA Séminaire en informatique cognitive/Cognitive Informatics Seminar Thursday, 10:30 am (Paris 16h30) November 3, 2022 Zoom: https://uqam.zoom.us/j/88481835073
Abstract: Machine learning algorithms are present in many of the applications and services we use every day. These technologies are often designed in isolation from their users, leading to a standardisation of their uses and a centralised control of their capabilities. Creating learning technologies that are closer to people and their context of use opens up the possibility of more responsive, appropriable and inclusive interactions. In this talk, I will present the context and the research community working on these themes at the intersection between HCI and AI. Then I will focus on my work in this field. I will show examples of research where the artistic approach is sometimes seen as a tool to reflect on technologies as cultural actors, and sometimes seen as a tool to inspire the design of rich and expressive interactions. Finally, I will present concrete ways to design interactions with machine learning algorithms through the concept of Machine Teaching.
Bio: Baptiste Caramiaux is a CNRS researcher at ISIR, Sorbonne Université in Paris, in the HCI Sorbonne group. He conducts research in human-computer interaction (HCI), studying and designing interactions with machine learning algorithms in the context of performing arts, health and pedagogy.
References:
Caramiaux, B., Altavilla, A., Françoise, J., & Bevilacqua, F. (2022, June). Gestural Sound Toolkit: Reflections on an Interactive Design Projecthttps://nime.pubpub.org/pub/vpgn52hr/release/1?readingCollection=8d5ef7ab. In International Conference on New Interfaces for Musical Expression. PubPub.
Caramiaux, B., Alaoui, S. F., & Hsueh, S. (2022, April). What Becomes of" Work" in AI" Artwork"https://scholar.google.com/scholar?as_ylo=2022&q=author:%22caramiaux+baptiste%22&hl=en&as_sdt=0,5?. In CHI'22 Conference-Workshop on Outsourcing Artificial Intelligence: Responding to the Reassertion of the Human Element into Automation.